The ‘Mind-Upload’ hypothesis (MU), a radical version of the Brainin-a-Vat thought experiment, asserts that a whole mind can safely be transferred from a brain to a digital device, after being exactly encoded into substrate independent informational patterns. Prima facie, MU seems the philosophical archenemy of the Embodied Mind theory (EM), which understands embodiment as a necessary and constitutive condition for the existence of a mind and its functions. In truth, whether and why MU and EM are ultimately incompatible is unobvious. This paper, which aims to answer both questions, will not simply confirm that MU and EM actually are incompatible. It will also show the true reason of their incompatibility: while EM implies that a mind’s individual identity is contingent upon the details of its physical constituents, MU presupposes that minds can be relocated from one material vessel to another. A systematic comparison between these conflicting assumptions reveals that the real shortcoming of MU is not the one usually discussed by the philosophical literature: it has nothing to do with MU’s functionalist or computationalist prerequisites, and is only secondarily related to the artificial implementability of consciousness; the real problem is that MU presupposes that minds could still be individuated and numerically identified while being reduced to immaterial formal patterns. EM seems committed to refute this assumption, but does it have sufficient resources to succeed?

Upshot: The computational theory of mind has been elaborated in many different ways throughout the last decades. In Explaining the Computational Mind, Milkowski defends his view that the mind can be explained as computational through his defense of mechanistic explanation. At no point in this book is there explicit mention of constructivist approaches to this topic. We will, nevertheless, argue that it is interesting for constructivist readers.

Fodor J. (1980) Methodological solipsism considered as a research strategy in cognitive psychology. Behavioral and Brain Sciences 3: 63–110.

The paper explores the distinction between two doctrines, both of which inform theory construction in much of modern cognitive psychology: the representational theory of mind and the computational theory of mind. According to the former, propositional attitudes are to be construed as relations that organisms bear to mental representations. According to the latter, mental processes have access only to formal (nonsemantic) properties of the mental representations over which they are defined. The following claims are defended: (1) That the traditional dispute between “rational” and “naturalistic” psychology is plausibly viewed as an argument about the status of the computational theory of mind. Rational psychologists accept a formality condition on the specification of mental processes; naturalists do not. (2) That to accept the formality condition is to endorse a version of methodological solipsism. (3) That the acceptance of some such condition is warranted, at least for that part of psychology which concerns itself with theories of the mental causation of behavior. This is because: (4) such theories require nontransparent taxonomies of mental states; and (5) nontransparent taxonomies individuate mental states without reference to their semantic properties. Equivalently, (6) nontransparent taxonomies respect the way that the organism represents the object of its propositional attitudes to itself, and it is this representation which functions in the causation of behavior. The final section of the paper considers the prospect for a naturalistic psychology: one which defines its generalizations over relations between mental representations and their environmental causes, thus seeking to account for the semantic properties of propositional attitudes. Two related arguments are proposed, both leading to the conclusion that no such research strategy is likely to prove fruitful.

Purpose of this paper – From the radical constructivist point of view the mainstream conception of memory as an encoding-storage-retrieval device is considered questionable. The paper aims at an alternative perspective on memory and its interaction with cognition. Design/methodology/approach – The argumentation is based on various experimental data such as cognitive problem-solving, change blindness, and childhood amnesia. Theoretical insights of the radical constructivist epistemology developed by Heinz von Foerster and others contribute as well. Findings: Describing memory as storage-retrieval device separated from cognition is rejected. Rather, memory is the expression of a static snapshot of otherwise dynamical cognitive processes. As an embodied network of constructive components, the evolutionary evolved cognition-memory compound is not geared toward reproducing “true” facts. Rather, its goal is to produce structure that maintains coherence with the rest of the network. Research limitations/implications – Memory research should not judge recognition in terms of “correct” or “false” but rather reassess its performance in terms of the super-ordinate cognitive faculty. Practical implications: The results imply that the role of memory should be reconsidered both in memory research as well as in practical areas such as psychotherapy and law. Originality/value – The new characterization of memory rejects the narrow computational theory of mind. It provides a better account for memory distortion phenomena such as false recognition, intrusion, and confabulation.

Context: Most constructivist discourse is situated at the philosophical-conceptual level, where arguments appeal to the intuition of the reader, while formal-computational models have only been taken into account to a very limited degree so far. Problem: Two types of problems need to be addressed: Synthetically, can constructivist concepts be turned into actual computational implementations? Can these be further conceptual developments in constructivist theory as such, or are they just an application thereof? Conceptually, does the notion of computation square with constructivist approaches at all? Method: Paradigmatically, we discuss the meaning of “computational” in cognitive agents that comply with constructivist concepts. Also, we summarize the contributions. Results: From a constructivist point of view, the concept of “computational model” is ambiguous and depends on whether it is used in the sense of the computational(ist) theory of mind or simply as a tool. Implications: The insights presented in the contributions to this special issue point in the direction of a computational extension of constructivist approaches as well as a constructivist extension to computational approaches. However, while many of the questions we posed were discussed in the contributions and open peer commentaries, some of them were largely neglected and thus are subject to further discussion.

Excerpt: There are two basic requirements for any paradigm in cognitive science: it must provide a genuine resolution of the mind-body problem, and it must provide for a genuine core articulation between a multiplicity of disciplines – at the very least between psychology, linguistics and neuroscience. Cognitive science owes its very existence to the fact the Computational Theory of Mind (CTM), whatever its defects and limitations, does fulfill these two requirements. In order even to get off the ground, any candidate for the role of an “alternative paradigm” must do at least as well as CTM in both these respects. The aim of this text is to explain how the proto-paradigm of enaction does just this.

Open peer commentary on the article “A Cybernetic Computational Model for Learning and Skill Acquisition” by Bernard Scott & Abhinav Bansal. Upshot: The Computational Theory of Mind suffers from an inherent weakness owing to its difficulty in taking semantics and embodiment properly into account. It is suggested that these difficulties could be alleviated if it were recognized that the fact that the model presented here employs a computer as a tool, to highlight certain key features of its dynamics, does not necessarily involve assuming that the underlying processes that are modelled are themselves strictly computational in nature.